“For the first time, we could compare product costs and capacity across all our European factories—and make allocation decisions based on data, not assumptions.”
— European Operations Director
The Challenge
A confectionery manufacturer with multiple European factories needed to understand the true performance and cost structure of their chocolate processing and packing operation. With six packing lines running dozens of product variants, decisions about which products to make where were based on historical allocation rather than current reality.
Senior management lacked visibility into how constraints at each production stage affected overall capacity. They couldn’t confidently answer fundamental questions: Which line is best suited for which product? What does each product actually cost to make? How does this facility compare with their other European sites? Without this clarity, asset utilisation remained below potential and product allocation was suboptimal.
The Solution
We built a comprehensive model of the chocolate processing and packing facility covering all six lines. The model captured every factor that drives cost and performance: material usage, throughput rates, buffer storage, efficiency, yield, waste, labour utilisation, energy consumption, and consumables—for all products across all lines in scope.
Constraint Identification
The model mapped constraints at each stage of the production process—from chocolate preparation through moulding, cooling, and packing. This revealed where bottlenecks were limiting throughput and where capacity was being underutilised. Some constraints were equipment-based, others were driven by changeover complexity or labour availability.
Buffer Storage Optimisation
By modelling the relationship between production schedules and material requirements, we identified opportunities to reduce inbound deliveries without risking line stoppages. Optimised buffer storage meant fewer deliveries, lower handling costs, and reduced warehouse complexity.
Production Scheduling
We generated production schedules that made best use of available assets, sequencing products to minimise changeover losses and balance workload across lines. The scheduling model accounted for real constraints—not theoretical capacity—to deliver plans that would actually work on the factory floor.
Cross-Factory Comparison
With accurate product costs and capacity data from this facility, senior management could compare performance against their other European factories. This enabled strategic decisions about product allocation—moving production to the site where it could be made most efficiently, rather than where it had always been made.
The Results
The model transformed operational visibility and strategic decision-making:
90% asset utilisation achieved through optimised production scheduling that made best use of all six packing lines.
7% reduction in inbound deliveries through optimised buffer storage, cutting logistics costs and warehouse handling.
Product-line allocation decisions now based on modelled performance data, enabling management to assign products to the most suitable lines.
Pan-European visibility allowing senior management to compare product costs and capacity utilisation across their factory network.
True product costing incorporating all operational factors, giving commercial teams accurate data for pricing and margin analysis.
The manufacturer shifted from site-by-site thinking to network-wide optimisation—making product allocation decisions based on evidence rather than legacy.